Fairness in AI for healthcare

Area of Science:

• Healthcare Technology
• Medical Ethics
• Computer Science

Background:

• Artificial intelligence (AI) offers transformative potential for healthcare delivery and patient outcomes.
• Concerns exist that AI may perpetuate or amplify existing health disparities.
• Understanding and addressing bias in healthcare AI is critical for equitable implementation.

Purpose of the Study:

• To discuss the pervasive issue of bias within healthcare artificial intelligence.
• To explore the potential for AI to exacerbate existing health inequities.
• To highlight ongoing and future research addressing bias in healthcare AI.

Main Methods:

• Literature review of AI in healthcare.
• Analysis of bias in AI algorithms.
• Synthesis of research on mitigation strategies.

Main Results:

• AI's dual potential: significant healthcare improvements versus exacerbation of disparities.
• Identification of key sources and types of bias in healthcare AI.
• Overview of emerging solutions and research directions for bias mitigation.

Conclusions:

• Addressing bias in healthcare AI is essential for equitable technology deployment.
• Continued research is vital to develop and implement fair and unbiased AI systems.
• Proactive strategies are needed to ensure AI benefits all patient populations.